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The classification algorithms to support the management of the patient with femur fracture.
- Source :
-
BMC medical research methodology [BMC Med Res Methodol] 2024 Jul 16; Vol. 24 (1), pp. 150. Date of Electronic Publication: 2024 Jul 16. - Publication Year :
- 2024
-
Abstract
- Effectiveness in health care is a specific characteristic of each intervention and outcome evaluated. Especially with regard to surgical interventions, organization, structure and processes play a key role in determining this parameter. In addition, health care services by definition operate in a context of limited resources, so rationalization of service organization becomes the primary goal for health care management. This aspect becomes even more relevant for those surgical services for which there are high volumes. Therefore, in order to support and optimize the management of patients undergoing surgical procedures, the data analysis could play a significant role. To this end, in this study used different classification algorithms for characterizing the process of patients undergoing surgery for a femoral neck fracture. The models showed significant accuracy with values of 81%, and parameters such as Anaemia and Gender proved to be determined risk factors for the patient's length of stay. The predictive power of the implemented model is assessed and discussed in view of its capability to support the management and optimisation of the hospitalisation process for femoral neck fracture, and is compared with different model in order to identify the most promising algorithms. In the end, the support of artificial intelligence algorithms laying the basis for building more accurate decision-support tools for healthcare practitioners.<br /> (© 2024. The Author(s).)
- Subjects :
- Humans
Female
Male
Aged
Femoral Fractures surgery
Femoral Fractures classification
Femoral Fractures therapy
Length of Stay statistics & numerical data
Artificial Intelligence
Middle Aged
Aged, 80 and over
Risk Factors
Algorithms
Femoral Neck Fractures surgery
Femoral Neck Fractures therapy
Femoral Neck Fractures classification
Subjects
Details
- Language :
- English
- ISSN :
- 1471-2288
- Volume :
- 24
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- BMC medical research methodology
- Publication Type :
- Academic Journal
- Accession number :
- 39014322
- Full Text :
- https://doi.org/10.1186/s12874-024-02276-5